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Generative AI Engineer with 1+ years in RAG pipelines, LLM-powered agentic workflows & intelligent d
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Generative AI Engineer with 1 year of industry experience building and deploying RAG pipelines, LLM-powered agentic workflows, and intelligent data retrieval systems in production environments. Proficient in LangChain, LangGraph, and FastAPI for software process automation across legal, financial, and enterprise domains. Experienced in deploying scalable AI-powered applications on cloud infrastructure using Docker and CI/CD pipelines, with hands-on expertise in vector databases (ChromaDB, FAISS) and VLM-based multimodal systems. Academic foundation in statistics and analytical modelling from an MA in Econometrics.
Brototype, Bengaluru
Data Science
August 1, 2023 – June 30, 2025
Mahatma Gandhi University
MA · Econometrics
August 1, 2020 – June 30, 2022
Mahatma Gandhi University
BSc · Mathematics
August 1, 2017 – June 30, 2020
Nxtgen Cloud Technologies
AI Engineer
April 1, 2025 – April 1, 2026
Bengaluru, Karnataka, India
English Mastery – AI-Powered Communication Assistant
June 24, 2026 – Present
Built a GenAI-powered intelligent agent using RAG, LangChain, and OpenAI embeddings for context-aware personalised communication support; deployed scalable FastAPI microservices backend on AWS with Docker and Kubernetes; integrated Whisper (speech-to-text) and GTTS (text-to-speech) for multimodal voice interaction. Designed test plans and built an evaluation framework using Jupyter Notebooks to benchmark response quality, hallucination rate, and latency across Gemini, LLaMA3, and GPT-3.5 (OpenAI API), enabling data-driven model selection and prompt engineering optimisation.
View ProjectAI Product Recommendation and Review Intelligence System
June 24, 2026 – Present
Designed a hybrid ML and GenAI agentic system to analyse large-scale customer reviews; built RAG pipelines with document chunking and indexing over structured (CSV, SQL) and unstructured datasets; applied sentiment analysis, logistic regression, and time series analysis to identify trends. Developed REST API dashboards in Streamlit following service-oriented design; integrated automated GenAI pipeline workflows for end-to-end inference and reporting; used Jupyter Notebooks for exploratory analysis and experiment tracking.
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from legal AI platforms to multimodal vision AI and hiring platforms, indicates adaptability and a broad interest in applying AI across different domains. Their experience in collaborative environments and focus on delivering production-ready solutions aligns well with a team-oriented, results-driven culture. The academic background in Econometrics and Mathematics, combined with practical AI engineering experience, suggests a strong analytical foundation and a continuous learning mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong operational fit through their experience with SDLC best practices, CI/CD, monitoring, and collaboration with cross-functional teams. Their project descriptions indicate a structured approach to problem-solving and a focus on measurable outcomes. The emphasis on evaluation frameworks and performance monitoring suggests a data-driven and quality-conscious mindset.